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Over the past five decades, fossil deposits within the Upper Burgi, KBS and Okote members at East Turkana in northern Kenya have provided many important insights into hominin behavior and ecology during a critical period in hominin evolution between 2.0 and 1.4Ma. In this study, we use a large compilation of faunal abundance data from paleontological and archaeological collections at East Turkana...
Healthcare systems are shifting from patient care in hospitals to monitored care at home. It is expected to improve the quality of care without exploding the costs. Remote patient management (RPM) systems offer a great potential in monitoring patients with chronic diseases, like heart failure or diabetes. Patient modeling in RPM systems opens opportunities in two broad directions: personalizing information...
We consider classification of sequential data in the presence of frequent and abrupt concept changes. The current practice is to use the data after the change to train a new classifier. However, if the window with the new data is too small, the classifier will be undertrained and hence less accurate that the "old'' classifier. Here we propose a method (called WR*) for resizing the training window...
Sales prediction is a complex task because of a large number of factors affecting the demand. We present a context aware sales prediction approach, which selects the base predictor depending on the structural properties of the historical sales. In the experimental part we show that there exist product subsets on which, using this strategy, it is possible to outperform naive methods. We also show the...
We look at binary online classification in the light of sudden concept drift (data exhibits non-stationarity). The accuracy of the classifier trained on a mixture of old and new data is compared to the accuracy of the classifier trained only on new data, assuming known point of concept drift. We employ a simplified model of concept drift and derive theoretical generalization error for the Euclidean...
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